The retail market has seen a significant amount of growth in online shopping since the advent of the Internet. On the Internet, users may search for, locate, and purchase nearly everything that can be purchased at a physical marketplace.
The difficulty for online shoppers has become identifying the product that they would like to purchase. With the rapidly multiplying outlets for purchasing products available online and the abundance of competing brands and model numbers within a brand, it can be difficult for a shopper to locate the product that he desires.
In many existing shopping search engines, the user will enter one or more keywords, and the search engine will offer a number of suggested queries to assist the user. The user may select one of the queries to enhance his search, or he may ignore them and continue the search with his own keyword selection. Currently, many search engines gather the suggested queries from the previous queries of other shoppers. However, these query suggestions based on historical search entries may not be effective as many shoppers are not knowledgeable enough about the product to enter useful queries. As a result, ineffective searches are repeated again and again by subsequent users.